A model of document clustering using ant colony algorithm and validity index

This paper discusses document clustering using ant colony algorithm and validity index. Clusterings are formed on the plane by ants walking, picking up or dropping down projected document vectors with different probability. The proposed model uses a clustering validity index not only to evaluate the performance of the algorithm, but also to find the optimal number of clusters and reduce outliers. Experiments on data from the Reuters-21578 collection show that the proposed model has better performance than that of LF algorithm and ART neural networks.